Computer Beats Go Champion
Koreantoast writes: Go (weiqi), the ancient Chinese board game, has long been held up as one of the more difficult, unconquered challenges facing AI scientists... until now. Google DeepMind researchers, led by David Silver and Demis Hassabis, developed a new algorithm called AlphaGo, enabling the computer to soundly defeat European Go champion Fan Hui in back-to-back games, five to zero. Played on a 19x19 board, Go players have more than 300 possible moves per turn to consider, creating a huge number of potential scenarios and a tremendous computational challenge. All is not lost for humanity yet: DeepMind is scheduled to face off in March with Lee Sedol, considered one of the best Go players in recent history, in a match compared to the Kasparov-Deep Blue duels of previous decades.
Looking forward to the future when this technology is a little bit important. Maybe 20 years. Congrats, Goople.
When I first read the headline, I pictured a robot's arms flailing about, whacking its human competitor upside the noggin. "So, A.I. finally got the emotion thing down."
Table-ized A.I.
You can make the go board as big as you want and make the move numbers huge on paper, but in reality I think you can reallly localize the areas you're playing in - really reducing the computational complexity.
For example, for the first move, you can slice the board up in 4 quadrants and any piece laid anywhere is going to have pretty much the same consequences as having put that piece in it's mirror position on the other 4 squares. And that will continue to being true pretty much as long as the players stick to that quadrant.
I suspect what really slowed down Go progress was that Chess was simply more popular and people in the west get wowed much more if you tell them a computer beat the best Chess champion vs the best Go champion. Corporations like IBM stick money into these projects for the publicity. Now that the east has money and marketshare...
This isn't AI. Neither is Siri. So you AI nutters need to just relax. There is no such thing as AI currently.
The moral of this story is, yes, Windows 10 might be pretty. Windows 10 might support all of your favourite games. But in 2016, there is nothing this OS does that Linux can not ..
There has never been less reasons to choose Windows over Linux, and therefore absolutely no reason that THIS should not be The belated year of the Linux Desktop. link
Evaluating every board combination to search-tree depth isn't intelligence. If anything, its a parlor trick that shows that a system with *absolutely no intelligence of its own whatsoever* can be designed to play a game with sufficient apparent skill that it can beat a human player.
When you are evaluating so many orders of magnitude more board combinations than a human could ever hope to, it seems inevitable that at some point, you will eventually find a tipping point that overwhelms human capacity to defeat. The degree to which I would suggest that this is progress towards machine intelligence is approximately the same as the fact that they can perform math operations billions of times faster than people too.
An intelligent game-playing system should not have to evaluate many more moves than the very best players in the world in order to beat anyone. If you want to build an intelligent system, figure out exactly how so few board combinations need to really be evaluated by people in order to play with high competency, and replicate *THAT*.
File under 'M' for 'Manic ranting'
Wake me when he beats Lee Sedol. There is a signficant difference in skill level between a European champion and someone like Lee Sedol.
what a name. like: Tiger Woods. sorry he got beat up. hope Computer is convicted.
Using well known and solid techniques along with vast computing power, Google has finally broken into the majors of Go. The next question is whether a home computer can run the neural network now that it's been trained;.. or do the CPU and RAM requirements still place this level of play into the corporate-only bracket.
Once we can run our own purpose-designed expert systems on commodity hardware, that's when the social change AI will bring will be nigh. Whether it's beneficial to everyone, to just the 1%, or whether everything goes tits-up I have no clue. But we aren't there yet, because things like this are still hugely expensive to train and operate. A government can make a single person fly with a jetpack, but that has had zero impact on our daily lives. Social change rarely occurs until revolutionary capabilities are available to the masses (or at least the small business owners).
"I will trust Google to 'do no evil' until the founders no longer run it." Hello Alphabet.
1) Trained a deep neural net to predict a human player's move. Correct predictions were 57% based off 30 million samples. The previous best was 44%.
2) Create a second deep neural net to determine the value of a board, meaning if you're winning or losing.
3) Use the two networks as the heuristics in a tree search.
4) Let the computer play itself to get better (basic reinforcement learning).
5) Have excellent hardware to run the tree search during a real game.
This is all standard AI stuff. Here's a quote from the article: "AlphaGo is a step toward an “enlightened” AI because, as Schaeffer says, AlphaGo is a first example of an AI with “general intelligence.”". Just disgusting. This AI has no general intelligence. The AI can't do anything but play Go. You'd have to retrain the nets for anything else. A general AI wouldn't need retraining, or at least no more than we do. They used a general AI algorithm combined with another general AI algorithm. You could take their combined algorithm and apply it to other things, but that does not equate to general intelligence.
Oooo, I'll make an AI with super intelligence by using three neural networks. 1 to predict moves, 1 to evaluate the current state, and the 3rd to estimate the value of 10-20 moves in the future. The 3rd will help in pruning more branches of the tree thus letting the AI search deeper and make better movies. Send me research money and fame!
I googled Fan Hui: one source says he's 8 dan amateur, another that he's 2 dan pro. That's only a little bit better than go programs have been for several years, and much weaker than the best professional players. If he's a top player in Europe, that mostly says that go isn't played at a very high level in Europe. I think that the progress that has been made on go software is really great, but the claim to have beat a 'go champion' seems a bit of a spin.
let's play global thermonuclear war
If the computer could beat a 2-dan professional, then it's clearly even smarter than SHODAN!
I'm a coder, and good poker player. I make the right decision a huge majority of the time, upwards of 95% of the time. If i spent a few weeks in java, I could make a winning poker bot vs most players. In poker, being the best isn't always about beating the best though. You want a bot that will play well vs the common styles other players do. I'm sure I could write a positive gain bot, but if you sat it down with pros, and they knew it was AI, they might be able to do well. Thats another thing in poker. The best player doesn't always win.
Videos are available.
a,e,i,o,u and sometimes w and y (at be if of up cwm by)
Poker is a game of incomplete knowledge - you don't know what cards are in the other players hands.
Go is a game of complete knowledge. As is chess. And draughts.
The two classes are completely different.
Birds are not dinosaur descendants;birds are dinosaurs, for all useful meanings of "birds", "are" and "dinosaurs"
I have some involvement in this field and I can't think of a single time I've seen the term AI in a book or research paper. The only time I ever see anyone use it is in the media or various futurists. Usually people just name their specific subfield or name the types or algorithms in which they specialize. "I specialize in unstable learners" or "I specialize in transfer learning" but I've never heard someone say "I specialize in AI."
I think naming neural networks as they did was probably a very bad idea. The mathematics have very little to do with actual neurons in the brain but the name leads you to believe differently.
Go, Deep Mind, Go!
poker cannot be solved. It is a game where you do not have complete information till the end of the hand, the best you can do is understand the odds of you being ahead and playing to those odds. That will work well against weak players and there are many bots made to farm those weak players. Against even above average players a bot playing to the odds will be demolished.
Computers have beaten higher-ranked players (Catalin Taranu, 5-p) on the 9x9 board. Computer go is nowhere near computer chess where humans cannot stand a chance against the top engines like Komodo, which is rated over 3300 ELO.
I cannot help but notice that Google are advertising their AI system, after IBM pushed Watson for years, and Microsoft have recently open-sourced their system:
https://github.com/Microsoft/CNTK/
I am curious though about the result against a 9-dan pro, and what will such a player say about the way the engine plays.
Of course you cannot "solve" poker or other games with randomness or hidden info in the sense of guaranteeing a win.
But that doesn't mean that such games cannot be solved in a more general optimization sense, e.g. maximizing your probability of winning a single match, or maximizing your expected monetary gain in poker.
E.g. consider a typical late endgame situation in Backgammon. You cannot "solve" it in the sense of guaranteeing a win. But clearly there is a "best move" in the sense of maximizing your probability of winning. And analogously backtracking to earlier moves.
He's probably about the standard of an International Master in chess. It's not the very top level, but probably only 3 stones from it. It's certainly no joke.
I would like to see the program play on, say, 17 x 17 so that a lot of the historical accounting would be taken away, and we could see how the raw strategy (i.e. tactics at a high rate of speed) work out.
No. Poker has a strong metagame. It matters not just that you understand how the game is played, but also how your opponent will play.
Strong AI poker players aren't getting better at doing the relatively simple maths of "what could happen?" but instead at figuring out patterns in their opponents play, and that includes what their opponents think of them. "I believe Player #4 has made a set here, so that wasn't just any call it was a Flat, and I should fold even though I'm getting 4:1, because I am a 10:1 dog to the set, and even though now they'll realise I know they had a set".
You pointed out a difference, but you failed to explain why it's relevant. One similarity is that in both cases we can objectively determine who's stronger with high probability given enough games. I think that the interesting fence is between "objectively" and "subjectively" determining the winner, not between "incomplete" and "complete" knowledge. So chess, go and poker are on one side, and music, art and poetry are on the other side.
tic-tac-toe is trivial to solve (I did so as a child -- there aren't very many moves) and, yes, the first player wins. Every time. Unless they're you, I guess.
The only winning move is not to play...
Please watch wargames scene...
You don't even need to proselytize for something already popular, right?
That is all...